Nonstationary Time Series Forecasting Using Wavelets and Kernel Smoothing

DOI10.1080/03610926.2010.529532zbMath1244.62131OpenAlexW2128074285MaRDI QIDQ2903836

Mina Aminghafari, Jean-Michel Poggi

Publication date: 2 August 2012

Published in: Communications in Statistics - Theory and Methods (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/03610926.2010.529532

zbMATH Keywords

nonstationarity

Mathematics Subject Classification ID

Inference from stochastic processes and prediction (62M20) Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Numerical methods for wavelets (65T60) Nonparametric inference (62G99)

Related Items (1)

A novel wavelet artificial neural networks method to predict non-stationary time series

Uses Software

• TDSL
• TSDL

Cites Work

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• Bandwidth selection for functional time series prediction
• A Functional Wavelet–Kernel Approach for Time Series Prediction
• Wavelets and their Applications
• Prediction Based on a Multiscale Decomposition
• FORECASTING TIME SERIES USING WAVELETS
• The elements of statistical learning. Data mining, inference, and prediction

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